2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)最新文献_第2页

Malware analysis and classification using Artificial Neural Network 基于人工神经网络的恶意软件分析与分类

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492653

A. Makandar, A. Patrot

{"title":"Malware analysis and classification using Artificial Neural Network","authors":"A. Makandar, A. Patrot","doi":"10.1109/ITACT.2015.7492653","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492653","url":null,"abstract":"Today major and serious threat on internet is malicious software or data which damage the system. Malware variants identification and classification is the one of the most important research problem in digital forensics. Malware binaries are set of instructions which may affect your system without your authority. Many researchers worked in this area mainly relied on specific API calls, sequences of bytes, statistic and dynamic analysis is used for detection and classification of malware. The proposed method malware is represented as 2Dimensional gray scale image is observed malware images of all the available variants and their texture similarity, which motivate to classify malware based on texture features. The texture plays a very significant role in identify and classify malware. The objective of this paper is to identify a behavior of malicious data based on global features using Gabor wavelet transform and GIST. The experiment done on Mahenhur dataset which includes 3131 binaries samples comprising 24 unique malware families. The algorithm has been implemented using feed forward Artificial Neural Networks (ANN) it gives their overview uniqueness. The experimental results are promising to effectively detecting and classifying malware with good accuracy 96.35 %.","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131388256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 67

K-Means based radial basis function neural networks for rainfall prediction 基于k均值的径向基函数神经网络的降雨预测

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492664

A. Dubey

{"title":"K-Means based radial basis function neural networks for rainfall prediction","authors":"A. Dubey","doi":"10.1109/ITACT.2015.7492664","DOIUrl":"https://doi.org/10.1109/ITACT.2015.7492664","url":null,"abstract":"Rainfall prediction problem has been one of the major issues of catchment management source water protection. Accurate rainfall prediction can be efficiently put to use by the agro based economy countries in terms of long term prediction. In this research work, a rainfall prediction model has been developed which uses K-Means clustering and artificial neural networks to fulfill the purpose. Artificial Neural Networks has been one of the major soft computing techniques used for the rainfall prediction since they are considered as one of the best function approximators. However, artificial neural networks have two issues which limit its applications, the computation complexity of the network and the learning time. In order to deal with these two issues, K-means clustering has been used in this work. Firstly, the data samples in this work are clustered using K means which cluster the samples according to their features. The number of clusters K has been computed using the Silhouette method. The clustered data samples are then used for training, validation and testing of different radial basis function neural networks. The results obtained from this method were then compared to the results obtained by only using a radial basis function neural network. For the comparison purpose, statistical criteria like Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Nash-Sutcliffe model efficient coefficient (E) and Correlation Coefficient (R) were used. It was observed that the results obtained by this method (R= 0.94587, E=0.90148) were better than only using RBFNN (R= 0. 88015, E=0. 82159).","PeriodicalId":336783,"journal":{"name":"2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114414206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Optimal allocation of distributed generators for minimizing the energy losses and maximizing the economic benefits considering cost of energy 考虑能源成本，以能量损失最小、经济效益最大化为目标对分布式发电机进行优化配置

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492695

Rekha C M, Madhuri Hombal, Shankarlingappa C B

引用次数: 0

Design of 4 bit flash ADC using TMCC & NOR ROM encoder in 90nm CMOS technology 采用90nm CMOS技术的TMCC和NOR ROM编码器设计4位闪存ADC

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492673

K. N. Hosur, Dariyappa, Shivanand, Vijay, Nagesha, G. V. Attimarad, H. Kittur

引用次数: 11

Analysis of electromagnetic wave propagation at discontinuities for different dielectric waveguide geometries using two-dimensional FEM 用二维有限元法分析不同介质波导几何形状的电磁波在不连续点上的传播

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492668

C. K, G. V. Attimarad

引用次数: 2

Development of automatic speech recognition system for voice activated Ground Control system 声控地面控制系统中自动语音识别系统的开发

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492684

S. Kavitha, S. Veena, R. Kumaraswamy

引用次数: 13

Study of high frequency characteristics of Metal Oxide Surge arrester 金属氧化物避雷器高频特性研究

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492694

A. M. Leela, V. Muralidhara, K. Ravi, N. Vasudev, R. Aradhya

引用次数: 3

Color image enhancement techniques in Wireless Capsule Endoscopy 无线胶囊内窥镜彩色图像增强技术

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492674

Vani V, K. Prashanth

引用次数: 9

A novel recognition of Indian bank cheques based on invariant geometrical features 基于不变几何特征的印度银行支票的新识别

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492682

Raghavendra S.P, A. Danti

引用次数: 5

3 axis SCARA robot with universal gripper 带通用夹持器的三轴SCARA机器人

2015 International Conference on Trends in Automation, Communications and Computing Technology (I-TACT-15) Pub Date : 2015-12-01 DOI: 10.1109/ITACT.2015.7492687

A. Balaji, Nippun Kumaar Aa, Sudarshan TSB

引用次数: 4